unskipped mobilenet_v3 quantization and mobilenet_v2 quantization plus tests from #125438 (#157786)

christinaburge · pytorchmergebot · commit 3a2c3c8ed365 · 2025-08-06T22:41:07.000Z
These tests now pass on AArch64 in our downstream CI. `test_quantization.py::TestNumericSuiteEager::test_mobilenet_v2 <- test/quantization/eager/test_numeric_suite_eager.py PASSED [2.4434s] [ 35%]` Pull Request resolved: #157786 Approved by: https://github.com/jerryzh168, https://github.com/malfet
diff --git a/test/quantization/eager/test_numeric_suite_eager.py b/test/quantization/eager/test_numeric_suite_eager.py
@@ -1,7 +1,6 @@
 # Owner(s): ["oncall: quantization"]
 # ruff: noqa: F841
 
-import unittest
 
 import torch
 import torch.ao.nn.quantized as nnq
@@ -38,7 +37,7 @@
     test_only_eval_fn,
 )
 from torch.testing._internal.common_quantized import override_qengines
-from torch.testing._internal.common_utils import IS_ARM64, raise_on_run_directly
+from torch.testing._internal.common_utils import raise_on_run_directly
 
 
 class SubModule(torch.nn.Module):
@@ -600,14 +599,12 @@ def compute_error(x, y):
         act_compare_dict = get_matching_activations(float_model, qmodel)
 
     @skip_if_no_torchvision
-    @unittest.skipIf(IS_ARM64, "Not working on arm right now")
     def test_mobilenet_v2(self):
         from torchvision.models.quantization import mobilenet_v2
 
         self._test_vision_model(mobilenet_v2(pretrained=True, quantize=False))
 
     @skip_if_no_torchvision
-    @unittest.skipIf(IS_ARM64, "Not working on arm right now")
     def test_mobilenet_v3(self):
         from torchvision.models.quantization import mobilenet_v3_large
 
diff --git a/test/test_linalg.py b/test/test_linalg.py
@@ -1401,8 +1401,6 @@ def run_test_case(input_size, ord, keepdim):
 
     @dtypes(torch.float, torch.double, torch.cfloat, torch.cdouble, torch.bfloat16, torch.float16)
     def test_vector_norm(self, device, dtype):
-        if IS_ARM64 and device == 'cpu' and dtype in [torch.float16, torch.bfloat16, torch.float32]:
-            raise unittest.SkipTest("Fails on ARM, see https://github.com/pytorch/pytorch/issues/125438")
         # have to use torch.randn(...).to(bfloat16) instead of
         # This test compares torch.linalg.vector_norm's output with
         # torch.linalg.norm given a flattened tensor
